Developing urbanization and changing hydrological conditions of natural streams increases the flooding risk. This study tries to do flood hazard zoning in the Ilam city and determine the critical area of the urban regions against flooding by using AHP method and GIS environment. For this purpose, the parameters of the curve number, height, distance from the river, geology, land use, population, slope, soil, building density, worn texture buildings and accumulated flow as effective parameters in flooding hazard in Ilam city selected and of these parameters weighted by using Expert Choice software. The result of the Expert Choice software is transferred to the environment of GIS software and flood hazard map of study area prepared. Results of the study and flood hazard map show that areas with very low-risk, low risk, intermediate-risk, high-risk and very high-risk form the 0. 8%, 8. 5%, 49. 6%, 32. 54% and 8. 56% of the of Ilam city area, respectively. Also, the central area of the city has the highest risk and the probability of occurrence of the flood due to the high density of population and residential areas in this area and its proximity to the seasonal rivers and old part of the city. Therefore, by examining the results of Expert Choice software, it is possible to identify the most effective factors in the occurrence of flood risk and prioritize them to address management solutions to eliminate or mitigate the effects of these factors.

Background and Objective: Inundation in urban areas due to dens storm has created many problems for all cities thorough the world. Urban flood hazard zoning may provide useful information for dealing with contingency and alleviating risk and loss of life and property. Therefore, in order to manage urban areas, take relief measures and prioritize areas to solve the problem of floods, the areas that are most affected should be identified. Method: Vulnerability of urban areas often includes multicriteria that are associated with flooding. One of the methods that are sufficiently accurate and available which can identify flood hazard zoning, is using multicriteria decision analysis (MCDA) that in this study was used to determine the potential of flood risk in urban area. Six variables include: distance to the main channel, slopes, land use, drainage density, slope of the main channel and elevation was used. After determining paired comparison matrix, layers weight was determined by using the knowledge of experts and experts in the region and finally the map of urban flood hazard were identified. Findings: Hazard Potential Map showed that 8. 2% of the areas near to the outlet and located around the main channel are at highest hazard potential. Discussion and Conclusion: The results and field investigation showed multicriteria decision analysis is accurate and appropriate method for urban flood hazard zoning and using this method can identify areas with a greater flooding risk.

The aim of this study is to assess effective factors in flooding and determine vulnerable areas in first and third Tehran Municipality areas, therefore suggest the proper management ways to avoid this disaster. Flooding disaster could have serious financial and fatal casualties, especially in urban areas. To reduce damages and hurts of flooding in these areas, hydrological, topographical, human features and …were used as separated layers in GIS and they were prioritized with a method like AHP. As the results areas with risks of flooding were determined. In this study the areas with high risks and low risks were recognized. Studying area was classified into five different classes and their areas were calculated. The very high risk area occurs in 16.21 km2 and respectively 19.11, 17.06, 9.67 and 1.84 km2 of areas were classified as high, medium, low and very low risks areas. By using this information, there could be proper plans and strategies to control floods and even utilizing flood water.

The occurrence of the flood is considered as one of the most important environmental hazards with high impact in urban areas that threatens the environment, human beings, and human assets permanently. In this research, using AHP model, fuzzy logic and its integration with GIS, the flood phenomenon in Lamerd city in the south of Fars province has been analyzed. For micro-zoning flood hazard, eight important criteria such as natural criteria (distance from the waterways, geology, and slope) and human criteria (road network, urban bridges, residential, agricultural and forest uses, land suitability) have been used. The results show that the flood-hazard area stretches in a broad strip along the northwest-southeast and covers most of Lamerd's urban area. This zone starts from the Zanganeh and Niraiee areas in the northwest of the Lamerd suburbs and includes Mohr-Lamerd highways, Ahmedabad and Ziarat areas. This area stretches along Motahari Street, Jomhuori Street and Moallem boulevard to the south end of the city of Lamerd. Therefore, an important part of Lamerd city and its suburbs are prone to flood hazard and at least half of the city is in a warning condition and the conditions of flooding is very possible.

In this research, the HEC-RAS model and its extension HEC-GeoRAS and their applications and capacities, as well as combination with the ArcView software, and introduced and flood zoning concerning the flood plain of Babolrood River was studied and damage to the plain as the result of floods was assessed. For this purpose, maps with 1:1000 scales were prepared and the study began in 103 sections within 5.5 km along the river. Hydrological data were collected and based on the Cawen method the roughness coefficient was determined in ten areas with approximate 500 meter distances between the points. Employing certain methods and operations, maps of the area, depth and velocity of floods in seven flood occurrences in 2, 5, 25, 50, 100 and 200 years ago were prepared, and damage to adjacent rice fields was assessed and related damage curves were drawn. The results had shown that about 89.53% of the flood area over past 200 years is prone to flooding according to the patterns in last 25 years. The damage curve shows that the rate of damage increases with the increase in the flooding depth up to the medium depth (2.82 m) while the damage rate decreases in medium depths more than 2.28 m. among Babolrood section 1, Babolrood section 2 and Sajjadrood, the highest depth of flooding is found in the Babolrood and the velocity of flooding in sections 1 and 2 of Babolrood is higher than the velocity in the Sajjadrood section.

Flood monitoring and zoning play an important role in reducing the damage caused by this natural crisis. The purpose of this paper is to investigate the risk of flooding of April 2019 in Khuzestan using Landsat-8 data. First, image processing was performed in ENVI 5. 3 software and then MNDWI and NDWI indices were used to monitor the floods. Then, the flood hazard map was prepared in ArcGIS10. 4 software. The results show that the southern and southwestern parts of the province are in a very severe situation and the central and southeastern parts are in a very hazardous condition, which is one of the most prone flood areas in the province. Also, monitoring of flood maps in Khuzestan province shows that there is a complete similarity between the recent flood and flood zoning map. Examination of the maps showing that the recent floods occurred mostly in the western, southern and southwestern parts. Spatial survey of floodplain areas shows that the cities of Hoveyzeh, Azadegan Plain, Ahvaz, Khorramshahr, Bandar Mahshahr, Abadan and especially Shadegan have been flooded more than other cities. Meanwhile, Shadegan city has been affected by floods based on MNDWI and NDWI indices of 191349 and 174813 hectares, respectively, which shows the highest rate compared to other cities in the province. In general, according to the results, the use of remote sensing data and MNDWI and NDWI indices for flood monitoring, as well as the use of geographic information system for flood risk zoning in related studies are recommended.

Floods have been considered the most common natural disaster worldwide in recent years. Flood hazard potential mapping is required for the management and mitigation of flood. Climatic change and the occupation of rivers and drainage have led to floods in arid areas. The objective of this study is to assess and zoning flood risk using the AHP-FUZZY hybrid approach model in the Dashti region of Bushehr Province.  In this study, precipitation, elevation, slope, drainage density, land use, geology and soil parameters were used. These parameters have been constructed and classified in the ARC GIS Software; which were weighed according to the AHP method in AHP SOLVER software and the layers were fuzzy using the fuzzy model. Finally, by combining the AHP-FUZZY method, the flood risk assessment and zoning map were obtained.6.5% of the area is in the very high-risk range, and 27.9% is in the high-risk range.  Analysis of the final map shows that Khormuj, Sana and Shonbeh are at greater risk of flooding. The combination of the AHP-FUZZY method in previous research has confirmed that this method has great capacity in flood risk assessment and zoning. Therefore, knowing the flood potential of the basin can be effective in formulating crisis management plans when faced with floods.

Flooding is one of the most significant natural disasters that has extensive impacts on various regions of Iran, particularly in Kashan County. Each year, this phenomenon causes considerable financial damage to local infrastructure and often results in human casualties. Given the importance of this issue, identifying and assessing flood-prone areas can play a crucial role in minimizing losses and preventing the destructive effects of floods. Accordingly, the present study focuses on flood susceptibility zoning in Kashan County, located in central Iran. In this research, Geographic Information System was employed as an effective analytical tool. In the first stage, raster maps related to key indicators influencing flood susceptibility were prepared. These indicators included environmental and geographical variables affecting flood occurrence. Subsequently, the maps were analyzed using the Analytical Hierarchy Process, one of the most widely used multi-criteria decision-making methods for weighting. The weights of each criterion and their respective classes were determined through this process. Finally, the flood susceptibility map was generated using the raster calculator tool within the GIS environment. The results indicate that approximately 30% of the county’s area falls within zones of high flood risk, primarily covering the eastern regions characterized by high population density and urban development. In contrast, about 60% of the area lies within low-risk zones, mostly located in the western parts of the county with gentle slopes and dense vegetation cover. The novelty of this study lies in the simultaneous integration of twelve environmental and hydrological indicators within the AHP-GIS framework, with a specific focus on the arid climatic conditions of Kashan. The findings of this research can serve as a valuable basis for disaster management planning and the implementation of preventive measures across Kashan County.

Due to the increase in the occurrence of floods, especially in the cities, and the emergence of human, financial, and environmental risks due to its increase, the flood zoning areas are of great importance. Therefore, in this study, it was tried zoning the areas of floods with the help of determining effective criteria. The criteria used in this research include Modified Fournier Index, Topographic Position Index, Curve Number, Flow Accumulation, Slope, Digital elevation model, Topographic Wetness Index, Vertical Overland Flow Distance, Horizontal Overland Flow Distance, and Normalized difference vegetation index. The novelty of this study is to present a new combination approach to determine the effective criteria in flood hazard zoning (Maneh and Samalqan County). In this regard, the combination of geographically weighted regression (Gaussian and tri-cube kernels) and binary particle swarm optimization algorithm was used. The recommended combination method is suitable for spatial regression problems because it is compatible with two unique properties of spatial data, i.e. spatial autocorrelation and spatial non-stationarity. The best value of the fitness function (1-R2) for Gaussian and tri-cube kernels were obtained 0.0745 and 0.0022, respectively, which indicates higher compatibility of the tri-cube kernel than the Gaussian kernel. It was also found that the criteria used have a significant effect on the rate of flooding in the study area.